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66 - This Map Predicts If You Get Sick In Kenya

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Manage episode 501100021 series 3661177
Content provided by WaterEngineer4Christ. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by WaterEngineer4Christ or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

❤️🔔 Subscribe 💧💬

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🎙️Follow on Podcast 🎧

https://open.spotify.com/show/1hdfOa8ZH1J1rq3lHi0sVw?si=MD0ZPdVnTseDWTDj_gPfZw

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⏰ 🕐Timestamp ⏲ 🕰

00:00 - Introduction

01:08 - The importance of sanitation for public health

02:35 - Defining "improved sanitation"

03:14 - The research goals: Mapping and quantifying sanitation access in Kenya

04:00 - Methodology: Combining survey data with high-resolution population maps

08:19 - Key findings: The stark link between wealth, location, and sanitation

10:17 - Population estimates and comparison with existing data

11:25 - Key takeaways and the importance of granular data

12:29 - Limitations of the study, including the challenge of GPS data shifting

13:53 - Conclusion: The value and future of high-resolution sanitation mapping

This study investigates the spatial distribution and estimation of access to improved sanitation in Kenya, utilizing household survey data from the 2008–2009 Kenya Demographic and Health Surveys and high-resolution population grids. The authors categorize households into wealth quintiles to observe disparities and apply spatial analysis methods, including excess risk, local spatial autocorrelation, and spatial interpolation, specifically Empirical Bayesian Kriging (EBK), to predict and map coverage rates. The study reveals significant disparities in sanitation access across different wealth categories and geographical regions within Kenya, with wealthier areas, particularly around Nairobi, exhibiting higher coverage. The findings suggest that future interventions should be tailored to specific wealth groups and areas with the greatest need to effectively improve sanitation access.

I hold a BSME and an MSME, and I am a Water Engineer by practice, trade, and research. Check out my article here:

https://iopscience.iop.org/article/10.1088/1748-9326/acb662

All the data I'm sharing comes directly from a peer-reviewed manuscript. For this educational review, I'm using brief quotations of the core findings—a common practice in articles and broadcasts. Of course, the source is linked for you below.

- 10.1371/journal.pone.0158490

#sanitation #kenya #education #podcast #health

#water #waterengineering #education #sdg6 #waterforall

  continue reading

202 episodes

Artwork
iconShare
 
Manage episode 501100021 series 3661177
Content provided by WaterEngineer4Christ. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by WaterEngineer4Christ or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

❤️🔔 Subscribe 💧💬

https://www.youtube.com/@greatcommissionerofking?sub_confirmation=1

🎙️Follow on Podcast 🎧

https://open.spotify.com/show/1hdfOa8ZH1J1rq3lHi0sVw?si=MD0ZPdVnTseDWTDj_gPfZw

Begin your Automation for your Contents here - referral code here with n8n:

https://n8n.partnerlinks.io/xgccuf14d16z

⏰ 🕐Timestamp ⏲ 🕰

00:00 - Introduction

01:08 - The importance of sanitation for public health

02:35 - Defining "improved sanitation"

03:14 - The research goals: Mapping and quantifying sanitation access in Kenya

04:00 - Methodology: Combining survey data with high-resolution population maps

08:19 - Key findings: The stark link between wealth, location, and sanitation

10:17 - Population estimates and comparison with existing data

11:25 - Key takeaways and the importance of granular data

12:29 - Limitations of the study, including the challenge of GPS data shifting

13:53 - Conclusion: The value and future of high-resolution sanitation mapping

This study investigates the spatial distribution and estimation of access to improved sanitation in Kenya, utilizing household survey data from the 2008–2009 Kenya Demographic and Health Surveys and high-resolution population grids. The authors categorize households into wealth quintiles to observe disparities and apply spatial analysis methods, including excess risk, local spatial autocorrelation, and spatial interpolation, specifically Empirical Bayesian Kriging (EBK), to predict and map coverage rates. The study reveals significant disparities in sanitation access across different wealth categories and geographical regions within Kenya, with wealthier areas, particularly around Nairobi, exhibiting higher coverage. The findings suggest that future interventions should be tailored to specific wealth groups and areas with the greatest need to effectively improve sanitation access.

I hold a BSME and an MSME, and I am a Water Engineer by practice, trade, and research. Check out my article here:

https://iopscience.iop.org/article/10.1088/1748-9326/acb662

All the data I'm sharing comes directly from a peer-reviewed manuscript. For this educational review, I'm using brief quotations of the core findings—a common practice in articles and broadcasts. Of course, the source is linked for you below.

- 10.1371/journal.pone.0158490

#sanitation #kenya #education #podcast #health

#water #waterengineering #education #sdg6 #waterforall

  continue reading

202 episodes

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